Learning to Quantify (LQ - also known as “quantification“, or “supervised prevalence estimation“, or “class prior estimation“, or “unfolding”) is the task of training class prevalence estimators via supervised learning. In other words, the task of these trained models is to estimate, given an unlabelled sample of data items and a set of classes, the prevalence (i.e., relative frequency) of each such class in the sample.

Learning to Quantify: Methods and Applications is a tutorial + workshop event co-located with the ECML/PKDD 2024 conference, and will take place on September 9-13, 2024, in Vilnius, Lithuania.